Atlantis is a whole-ecosystem simulation and a management strategy evaluation --- simulating the fisheries (or other industries) monitoring, assessment, management, and implementation processes, along with their various feedbacks on simulated Bay populations. The model integrates spatially-explicit information about the geochemical, biological, and physical factors that drive the ecosystem. The approach is designed to provide resource managers with science-based predictions for different management choices within an ecosystem context. Atlantis facilitates direct comparison of tradeoffs in various ecosystem services among different management scenarios, and quantifies relationships between habitat and fisheries resources. In this presentation, I will describe the basic model framework and then describe the application currently being developed for the Chesapeake Bay, referred to as the "Chesapeake Atlantis Model" (CAM). Extensive sensitivity analyses are planned for CAM, but once the model is perceived useful in capturing and predicting essential Bay dynamics, it should be a valuable tool for identifying critical information gaps, for assisting managers in prioritizing research, for providing supplementary information that complements traditional single-species stock assessment, and for research scientists in testing and generating research hypotheses about the Chesapeake Bay ecosystem and its populations. Information on CAM is available at: http://chesapeake.noaa.gov/ecosystem-modeling/chesapeake-atlantis-model- .

Dr. Ihde is leading the NOAA Chesapeake Bay Office's Ecosystem Modeling Team's effort to develop a spatially-explicit ecosystem-based fisheries management model for the Chesapeake Bay and its watershed using the Atlantis modeling approach. He earned his Ph.D. in the stock assessment of marine crustacean fisheries and his M.S. in marine science from the Virginia Institute of Marine Science at the College of William & Mary, and he has worked extensively on fisheries surveys in the Chesapeake Bay. His post-doctoral work at the University of Maryland's Chesapeake Biological Lab centered on the development of a new management process to effectively incorporate stakeholder knowledge and preference into the council-based fisheries management process of the US.

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